中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Analyzing and optimizing yield formation of tomato introgression lines using plant model

文献类型:期刊论文

作者Kang, Mengzhen1,6; Wang, Xiujuan1,7; Qi, Rui2; Jia, Zhi-Qi3; de Reffye, Philippe4; Huang, San-Wen5
刊名EUPHYTICA
出版日期2021-06-01
卷号217期号:6页码:17
关键词GreenLab model Yield formation Parameter estimation Tomato introgression line Optimization
ISSN号0014-2336
DOI10.1007/s10681-021-02834-8
英文摘要

Generally, the relation between quantitative trait loci (QTLs) and yield is empirical, and their roles in source-sink dynamics are unclear. A tomato introgression line (IL) population (S. pennellii ILs) was applied to analyze the effect of chromosome segment from wild cultivar on numerous yield-related phenotypes, including plant yield, the weight of vegetative part, the number and weight of individual fruits. A functional-structural plant model was applied to analyze the difference in yield formation of tomato ILs. Measurements on organ biomass were performed at four stages during the growth period of plants. Source and sink parameters were estimated from the experimental measurements of different organs for each IL, discovering how the final yield is linked to the fruit number, size and expansion process. The correlation and distribution of source-sink parameters for ILs were analyzed. The sink parameters were optimized to find a better combination of ILs to improve the yield using Particle Swarm Optimisation (PSO) algorithm. Optimization results indicate a potential yield increase of 35% for the control M82. This model-assisted analysis provides a promising approach to deeper insight in phenotypic data.

WOS关键词FUNCTIONAL-STRUCTURAL MODEL ; LYCOPERSICON-PENNELLII ; FRUIT SIZE ; NATURAL VARIATION ; GROWTH ; LEAF ; GREENLAB ; IDENTIFICATION ; MORPHOGENESIS ; RESPONSES
资助项目Natural Science Foundation of China[62076239] ; Natural Science Foundation of China[31700315] ; Chinese Academy of Science (CAS)-Thailand National Science and Technology Development Agency (NSTDA) Joint Research Program[GJHZ2076]
WOS研究方向Agriculture ; Plant Sciences
语种英语
WOS记录号WOS:000646556800001
出版者SPRINGER
资助机构Natural Science Foundation of China ; Chinese Academy of Science (CAS)-Thailand National Science and Technology Development Agency (NSTDA) Joint Research Program
源URL[http://ir.ia.ac.cn/handle/173211/44491]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
通讯作者Wang, Xiujuan
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Amadeus, 485 Route Pin Montard, F-06410 Biot, France
3.Coll Hort Henan Agr Univ, Zhengzhou 450002, Peoples R China
4.Univ Montpellier, CNRS, AMAP, CIRAD,INRA,IRD, F-34000 Montpellier, France
5.Chinese Acad Agr Sci, Agr Genomes Inst Shenzhen, Shenzhen 518124, Peoples R China
6.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100949, Peoples R China
7.Chinese Acad Sci, Beijing Engn Res Ctr Intelligent Syst & Technol, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Kang, Mengzhen,Wang, Xiujuan,Qi, Rui,et al. Analyzing and optimizing yield formation of tomato introgression lines using plant model[J]. EUPHYTICA,2021,217(6):17.
APA Kang, Mengzhen,Wang, Xiujuan,Qi, Rui,Jia, Zhi-Qi,de Reffye, Philippe,&Huang, San-Wen.(2021).Analyzing and optimizing yield formation of tomato introgression lines using plant model.EUPHYTICA,217(6),17.
MLA Kang, Mengzhen,et al."Analyzing and optimizing yield formation of tomato introgression lines using plant model".EUPHYTICA 217.6(2021):17.

入库方式: OAI收割

来源:自动化研究所

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